Investigating the Advantages of Magnetomyography in Assistive Healthcare Technology

Abstract

Assistive healthcare technologies and prosthetics are crucial for individuals with muscle impairments. In 2005, the number of limb losses from trauma exceeded 700,000, projected to double by 2050, affecting approximately 1,326,000 civilians. Understanding the fundamental principles of muscle function, therefore, is key to developing innovative assistive technologies that can improve the quality of life for people with disabilities. Surface electromyography (sEMG), measuring electrical muscle activity, has long been a common tool in assistive technologies, but various obstacles have limited its widespread application. Capturing sEMG signals via the skin and subcutaneous fat poses a main challenge as they act as a low-pass filter and lead to the loss of critical information. Thus, new alternative technologies are needed to address this challenge. Magnetomyography (MMG) is a technology that can noninvasively measure magnetic muscle signals. Unlike sEMG, MMG signals are not affected by various tissues as they are transparent for magnetic signals. This paper presents the fundamental scenarios, including fat thickness on the EMG and MMG signals, with finite element (FE) simulations using COMSOL. The effects of 50-750 µm fat on the recorded electrical and magnetic signals have been evaluated. The results indicate that by increasing fat thickness to 250 µm, the electrical signals decrease 66%, while MMG signals decline by 12%. Hence, the MMG can provide more accurate measurements of muscle activity for control strategies in prosthetic limbs.